R Notebook

Homework 5

library(nycflights13)
library(tidyverse)
library(ggplot2)

flights

filter(flights, month == 1, day == 1)

jan1 <- filter(flights, month == 1, day == 1)
(dec25 <- filter(flights, month == 12, day == 25))

df <- tibble(x = c(1, NA, 3))
filter(df, x > 1)

filter(df, is.na(x) | x > 1)

Exercise 5.2.4

question 1

#arrival delay 2 or more hours
filter(flights, arr_delay >= 120)

#flew to Houston (IAH or HOU)
filter(flights, dest == "IAH" | dest == "HOU")

#Were operated by United, American, or Delta
filter(flights, carrier == "UA" | carrier == "AA" | carrier == "DL")

#Departed in summer (July, August, and September)
filter(flights, month == 7 | month == 8 | month == 9)

#Arrived more than two hours late, but didn’t leave late
filter(flights, arr_delay > 120 & dep_delay == 0)

#Were delayed by at least an hour, but made up over 30 minutes in flight
filter(flights, dep_delay >= 60 & arr_delay <= 30) 

#Departed between midnight and 6am (inclusive)
filter(flights, dep_time >= 0 & dep_time <= 600)

question 2

?between()
filter(flights, between(flights$dep_time, 0, 600))

Between takes values inclusive of two boundary values. ie x >= left & x <= right, yes you can use it to simplify part 7 of question 1.

question 3

filter(flights, is.na(dep_time))

8,255 flights have NA dep_time.

question 4

NA….

Exercise 5.3.1

question 2

arrange(flights, desc(is.na(flights$dep_time)))

question 2

# most delayed flights
arrange(flights, desc(dep_delay))

# ealiest leaving
arrange(flights, dep_time)

question 3

# fastest flights
arrange(flights, air_time)

question 4

# farthest distance
arrange(flights, distance)

#shortest
arrange(flights, desc(distance))

Exercise 5.4.1

question 1

# how many ways to select columns dep_time, dep_delay, arr_time, arr_delay
select(flights, dep_time, dep_delay, arr_time, arr_delay)

select(flights, dep_time:arr_delay )

# select(flights, -everything not those)
select(flights, contains("arr"), contains("dep"))

questions 2

select(flights, arr_delay, arr_delay)

only comes up once!

question 3

# what does one_of do
?one_of
vars <- c("year", "month", "day", "dep_delay", "arr_delay")
select(flights, one_of(vars) )

Allows you to find variables that are contained in a character vector and apply it to select

question 4

select(flights, contains("TIME"))

?select
select(flights, ignore.case = FALSE, contains("TIME"))

Error: All select() inputs must resolve to integer column positions.
The following do not:
*  FALSE

does not worry about case, but this can be changes by, ignore.case = FALSE

Exercise 5.5.2

question 1

question 2

In air is much larger than the actual air time, this might be because dep time and arr time are not in units of minutes, but air_time is. You would have to change the units of the arr time and dep time to minutes

question 3

The dep delay should equal the difference of dep time and scheduled dep time.

question 4

Puts every tie to the lowest rank